samsung SM-S9380
Geekbench AI Score
2929
Single Precision Score
2928
Half Precision Score
5313
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 02 2025 07:25 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S9380 |
| Model ID | samsung SM-S9380 |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 14.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2012
374.1 IPS |
|
|
Image Classification (HP)
|
100% |
2112
392.8 IPS |
|
|
Image Classification (Q)
|
100% |
4478
832.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2560
41.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2458
39.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
5441
88.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5831
6.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
5676
6.62 IPS |
|
|
Pose Estimation (Q)
|
84% |
14321
17.0 IPS |
|
|
Object Detection (SP)
|
98% |
1757
139.9 IPS |
|
|
Object Detection (HP)
|
98% |
1778
141.5 IPS |
|
|
Object Detection (Q)
|
83% |
4122
332.9 IPS |
|
|
Face Detection (SP)
|
100% |
4564
54.2 IPS |
|
|
Face Detection (HP)
|
100% |
4574
54.4 IPS |
|
|
Face Detection (Q)
|
95% |
10078
120.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
4766
36.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
4730
36.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
10912
99.9 IPS |
|
|
Style Transfer (SP)
|
89% |
11876
15.4 IPS |
|
|
Style Transfer (HP)
|
89% |
11913
15.5 IPS |
|
|
Style Transfer (Q)
|
98% |
25543
32.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2457
90.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2466
91.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6805
252.2 IPS |
|
|
Text Classification (SP)
|
100% |
993
1.33 KIPS |
|
|
Text Classification (HP)
|
99% |
999
1.33 KIPS |
|
|
Text Classification (Q)
|
88% |
1091
1.47 KIPS |
|
|
Machine Translation (SP)
|
100% |
1401
24.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1396
24.0 IPS |
|
|
Machine Translation (Q)
|
50% |
598
21.2 IPS |
